ELPIS Lab

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UH200B, Unity Hall

100 Institute Rd

Worcester, MA 01609

Wecome to the webpage of the Efficient Learning and Planning for Intelligent Systems (ELPIS) Lab!

The Lab has a broad interest in autonomous robotic systems capable of reasoning about and interacting with the physical world. The primary goal is to develop agents that are efficient, robust, and capable of learning from real-world interactions. Current research projects focus on the integration of classical planning algorithms and state-of-the-art machine learning techniques, aiming to advance 1) planning efficiency, 2) planning robustness, and 3) planning from visual inputs.

If you are interested in joining the Lab please see this page.

news

Nov 14, 2024 Prof. Chamzas gave a talk at the UNH Robotics Seminar on “Learning and Planning for Robotic Manipulation: Bringing Theory to Practice.”
Aug 15, 2024 Two new Ph.D. students, Abhiroop Ajith and Ali Golestaneh, are joining the ELPIS lab!
Aug 01, 2024 The first paper of the ELPIS Lab titled “Expansion-GRR: Efficient Generation of Smooth Global Redundancy Resolution Roadmaps” has been accepted to IROS2024! Congrats Zhuoyun Zhong!
Jan 20, 2024 Our preprint manuscript on Computing Efficient Global Redundancy Resolution Maps is available on Arxiv: